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DOE OSTI2024

Qualitative and Quantitative Evaluation for Representative Human Reliability Analysis Methods

The Korea Institute of Nuclear Safety (KINS) is the regulatory expert organization established by the Korean government to strengthen the nation’s technical capabilities relating to nuclear safety regulation. KINS oversees the technical aspects of nuclear safety regulation, including safety reviews, inspections, education, and safety research—all conducted based on technical knowledge and accumulated regulatory experience. In 2023, KINS requested that Idaho National Laboratory (INL) validates representative human reliability analysis (HRA) methods used throughout the world, thus affording KINS with a basis for determining an HRA method adequate for its domestic regulatory purposes. The present paper mainly examines INL’s efforts in this regard. The resulting INL study covered four representative HRA methods widely used by nuclear utilities and regulatory institutes. These methods were qualitatively evaluated by applying specific evaluation criteria and determining how well each method reflected critical HRA issues. For this assessment, INL benchmarked the Halden International HRA Empirical Study. Using the Halden empirical data, along with information on human failure events (HFEs), the present study employed the selected HRA methods to estimate human error probabilities (HEPs) for the HFEs. It also performed statistical analyses to compare the HEPs predicted via the HRA methods against those from the Halden empirical data.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2021

Machine Learning Using Rapidity-Mass Matrices for Event Classification Problems in HEP

In this work, supervised artificial neural networks (ANN) with rapidity–mass matrix (RMM) inputs are studied using several Monte Carlo event samples for various pp collision processes. The study shows the usability of this approach for general event classification problems. The proposed standardization of the ANN feature space can simplify searches for signatures of new physics at the Large Hadron Collider (LHC) when using machine learning techniques. In particular, we illustrate how to improve signal-over-background ratios in the search for new physics, how to filter out Standard Model events for model-agnostic searches, and how to separate gluon and quark jets for Standard Model measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Event-Based Analysis of Solar Power Distribution Feeder Using Micro-PMU Measurements

Solar distribution feeders are commonly used in solar farms that are integrated into distribution substations. In this paper, we focus on a real-world solar distribution feeder and conduct an event-based analysis by using micro-PMU measurements. The solar distribution feeder of interest is a behind-the-meter solar farm with a generation capacity of over 4 MW that has about 200 low-voltage distributed photovoltaic (PV) inverters. The event-based analysis in this study seeks to address the following practical matters. First, we conduct event detection by using an unsupervised machine learning approach. For each event, we determine the event’s source region by an impedancebased analysis, coupled with a descriptive analytic method. We segregate the events that are caused by the solar farm, i.e., locallyinduced events, versus the events that are initiated in the grid, i.e., grid-induced events, which caused a response by the solar farm. Second, for the locally-induced events, we examine the impact of solar production level and other significant parameters to make statistical conclusions. Third, for the grid-induced events, we characterize the response of the solar farm; and make comparisons with the response of an auxiliary neighboring feeder to the same events. Fourth, we scrutinize multiple specific events; such as by revealing the dynamics to the control system of the solar distribution feeder. The results and discoveries in this study are informative to utilities and solar power industry.

14 SOLAR ENERGY↗

DOE OSTI2025

MOSAiC studies of long-lasting mixed-phase cloud events and analysis of the liquid-phase properties of Arctic clouds

Vertically resolved observations of the temporal evolution of mixed-phase clouds (MPCs) were performed over the central Arctic during the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition, which lasted from October 2019 to September 2020. The research icebreaker Polarstern , drifting with the pack ice for more than 7 months, mostly at latitudes > 85° N, served as a platform for state-of-the-art remote sensing of aerosols and clouds. The use of the recently introduced dual field-of-view (FOV) polarization lidar technique in combination with the well-established lidar-radar retrieval technique provided, for the first time, a robust instrumental basis to monitor the evolution of the liquid and the ice phase of MPCs and the interplay between the two phases. Two long-lasting Arctic MPC events observed close to the North Pole in mid-winter (December 2019) and late summer (September 2020) are discussed to provide new insight into Arctic MPC evolution processes. In the second part of the article, cloud statistics, covering all seasons of a year, are presented. The focus is on the optical and microphysical properties of the liquid phase. These results are solely derived from the dual-FOV lidar observations. The key findings of the study can be summarized as follows: persistent activation of aerosol particles to form water droplets is of great importance for the longevity of MPCs. The observations confirm that ice formation occurs predominantly via immersion freezing. The field studies suggest that the free tropospheric reservoirs of cloud condensation nuclei (CCN) and of ice-nucleating particles (INPs) were always well filled, i.e., the clouds did not exhaust their supply of activatable and activated particles. The observation of long-lasting MPC events, low ice production rates, and a sufficiently large INP reservoir leads to the recommendation to use a time-dependent immersion freezing parameterization in MPC modeling efforts.

Jimenez, Cristofer [Leibniz Inst. for Tropospheric↗

DOE OSTI2020

Enhanced Dynamic Equivalent Identification Method of Large-Scale Power Systems Using Multiple Event

The increasing complexity of the interconnected power system makes high-fidelity dynamic simulation models computationally more intensive. To improve computation efficiency, model reduction techniques have been investigated to only preserve the dynamics in a limited area of interest (study area), while deriving equivalent representation for the external area. For this purpose, a measurement-based reduction approach using system identification techniques has been previously proposed. In that case, external areas are represented by dynamic equivalent loads using transfer function estimation. In this paper, in order to enhance the accuracy of the reduced model in preserving dynamics of the study area, multiple “grid” events of different types and at different locations are considered for identifying the parameters of the equivalent loads. Case studies are carried out in the NPCC 140-bus system. Comparison are made between multiple events training and single event training, highlighting the advantages of the proposed method in providing a better representation of the grid dynamics under different operating conditions.

Xue, Yaosuo↗

DOE OSTI2023

Natural Language Processing for Text Based Event Extraction: Identifying Events of Interest Related to Worldwide State-Sponsored Civil Nuclear Power

Beginning in FY20, SRNL was funded by the National Nuclear Security Administration’s Office of Defense Nuclear Non-Proliferation Research and Development to develop a prototype natural language processing/natural language understating machine learning-based modeling and analysis pipeline to extract and forecast events of interest from massive open data sources. The working hypothesis within the approach is that contextual shifts in key words and phrases act as indicators of events of interest over time. Therefore, by identifying points in time where contextual shifts occur, events of interest can be extracted along with explicit and implicit connections of entities and activities. The development of the preliminary prototype pipeline proved successful, meriting further testing of the pipeline on more broad topical domains and in a worldwide data environment. Therefore, SRNL, in collaboration with the Sanghani Center for Artificial Intelligence and Data Analytics at Virginia Tech, have continued development with a test case of identifying events of interest related to worldwide state-sponsored civil nuclear power in open data sources. In the first year of this follow-on effort, the team has curated domain-specific data corpuses using an automated scheme and applied the modeling and analysis pipeline. This robust, focused, and efficient approach consists of an ensemble of analyses applied to time dependent word embedding models that are trained on the data corpuses. In this report, the team has demonstrated the capability of the existing pipeline (as development has continued in parallel) by exploring several specific case-studies centered around Rosatom’s international activities regarding the planning, construction, operation, and/or shutdown of nuclear reactors. A basic timeline events has been generated by manually cataloging known “milestone” events that have occurred at reactors in Turkey, Finland, Hungary, and Egypt and compared with the output of the modeling pipeline. In this approach, the team has characterized the lead time using the prototype pipeline, as well as the ability to capture relevant information, which proved 100% successful. A deep dive example of the Akkuyu reactor (Turkey) is presented that shows the breadth of information that can be captured using the approach. In this case study, events were extracted pertaining to the planning/construction of Akkuyu including protests from the population, information campaigns in response to the protests, forged regulatory documents and lawsuits, budgetary/shareholder information, geopolitical tensions, and the various construction milestones. This has demonstrated the pipeline’s utility as a research aid or real-time event extraction tool, where summary-level information and detailed text extractions from millions of articles or Tweets across long time periods can be generated with significantly less effort than current techniques.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

Enhanced dynamic equivalent identification method of large-scale power systems using multiple events

The increasing complexity of the interconnected power system makes high-fidelity dynamic simulation models computationally more intensive. To improve computation efficiency, model reduction techniques have been investigated to only preserve the dynamics in a limited area of interest (study area), while deriving equivalent representation for the external area. For this purpose, a measurement-based reduction approach using system identification techniques has been previously proposed. Accordingly, external areas are represented by dynamic equivalent loads using transfer function estimation. In this paper, in order to enhance the accuracy of the reduced model in preserving dynamics of the study area, multiple “grid” events of different types and at different locations are considered for identifying the parameters of the equivalent loads. Additionally, case studies are carried out in the NPCC 140-bus system. Comparisons are made between multiple events training and single event training, highlighting the advantages of the proposed method in providing a better representation of the grid dynamics under different operating conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Study of Stratus-Lowering Marine-Fog Events Observed During C-FOG

Two stratus lowering marine fog events observed on 28 September and 04 October 2018 during the Coastal Fog (C-Fog) field campaign that took place offshore of Eastern Canada during 1 September to 6 October 2018 are described. In-situ, profiling and remote sensing observations were made at selected land sites in eastern Newfoundland (NL) and Nova Scotia (NS) as well as aboard the research vessel (R/V) Hugh R. Sharp that cruised in adjoining coastal waters. Synoptic scale analysis showed that both fog episodes were an outcome of the interaction between synoptic-scale surface level low-pressure systems and a contiguous high-pressure system. At the same time, back trajectories revealed that the bulk of the fog layer is formed due to differential advection. Here, the diameter of the fog droplets at the surface gradually decreased from the centre of the fog layer to its leading/trailing edges. The bimodal fog droplet diameter distribution with peaks at 5-10 µm and 20-25 µm provided clues on droplet collision and coalescence processes. The observed difference between microphysical variables and droplet distribution between the two fog events and within same fog layer may have been governed by atmospheric boundary layer conditions (e.g., humidity conditions and turbulence) prevailed in the fog layer. Overall, it is concluded that the life cycle of observed stratus-lowering coastal-fog episodes is dependent on synoptic conditions as well as atmospheric boundary layer characteristics such as stability, cloud top cooling and entrainment.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Study of same-sign W boson scattering and anomalous couplings in events with one tau lepton from pp collisions at $\sqrt{s}=13$ TeV

A first study is presented of the cross section for the scattering of same-sign W boson pairs via the detection of a τ lepton. The data from proton-proton collisions at the center-of-mass energy of 13 TeV were collected by the CMS detector at the LHC, and correspond to an integrated luminosity of 138 fb −1 . Events were selected that contain two jets with large pseudorapidity and large invariant mass, one τ lepton, one light lepton (e or μ), and significant missing transverse momentum. The measured cross section for electroweak same-sign WW scattering is $1.44^{+0.63}_{-0.56}$ times the standard model prediction. In addition, a search is presented for the indirect effects of processes beyond the standard model via the effective field theory framework, in terms of dimension-6 and dimension-8 operators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

A Unified Model of Cosmic-Ray Propagation and Radio Extreme Scattering Events from Intermittent Interstellar Structures

Intermittent magnetic structures are a plausible candidate for explaining cosmic-ray (CR) diffusion rates derived from observed CR energy spectra. Independently, studies of extreme scattering events (ESEs) of radio quasars and pulsar scintillation have hinted that very straight, large aspect ratio magnetic current sheets may be responsible for the localized large scattering of radio waves. The required shortest axis of the typical structures producing ESEs is of the same scale (∼au) as the gyroradii of ∼GeV CRs. In this Letter, we propose that the same magnetic/density sheets can produce large scattering of both CRs and radio waves. We demonstrate that the geometry and volume-filling factor of the sheets derived from quasar ESEs can explain the observed mean free path of GeV CRs without introducing free parameters. The model places constraints on the sheet geometry, such as straightness and large aspect ratio, and assumes that the statistics of the sheets are similar throughout the Galactic volume. We therefore discuss observational tests of the sheet model, which includes observations of echoes in pulsars and fast radio bursts, gravitationally lensed quasars, the distribution of ESE durations, and spatial correlations between ESE events and rotation measure fluctuations. Such tests will be enabled by upcoming wide-field radio instruments, including the Canadian Hydrogen Observatory and Radio-transient Detector and Deep Synoptic Array 2000 Antennas.

Kempski, Philipp [Princeton Univ., NJ (United Stat↗

DOE OSTI2025

Propagating synthetic populations with dynamic Bayesian networks: a framework for long-horizon demographic forecasting

This study presents a dynamic demographic microsimulator using dynamic Bayesian networks to forecast long–term changes in household and individual life events. Leveraging longitudinal Panel Study of Income Dynamics (PSID) data, two networks for individuals and households were modeled to simulate transitions in employment, income, education, marriage, childbirth, leaving the parental home, home ownership, mortality, and household formation or dissolution. Across 1,000 simulation runs spanning 24 years, household–level outcomes remain highly accurate and individual–level predictions reasonable. Although accuracy naturally declines with projection horizon, performance remains promising at both levels. This study addresses a key limitation of existing population synthesis models, which typically generate only a single static snapshot of the population. In conclusion, by introducing a framework that propagates cross-sectional outputs into the future, the microsimulator enables the tracking of demographic evolution over time, enhances realism in population-based simulations, and supplies credible inputs to agent-based travel demand models.

Demographic modeling↗

DOE OSTI2021

Feasibility Study of Developing Alternative Common-Cause Failure Model for Event Assessment

This report is a revision of the original report, INL/LTD-14-33376. The original report, which was a limited distribution to the Nuclear Regulatory Commission (NRC) only and not available to the public, was revised as this report for public distribution. The report presents the feasibility study of alternative common-cause failure (CCF) models that could be used for event assessment in the Standardized Plant Analysis Risk (SPAR) models. The current CCF model used by the SPAR models is the alpha factor model. The proposed alternative CCF models are the partial alpha factor model and general dependency model. These alternative CCF models are reviewed and compared to the current alpha factor model, with the partial alpha factor model being identified as the preferred CCF model that could be used for event assessment in the SPAR models.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2024

The Potential for Solar Farms to Protect Crops Against Extreme Weather Events

With climate change posing serious risks to crop production, solar PV has the potential to protect agriculture against extreme climate events. This concept has significant implications for agrivoltaics, but large gaps exist in the physical understanding of the climate resiliency that solar PV can bring to agriculture, and current studies focus on one-off designs ideal to protect against specific climate events. This study investigates key climate events that threaten agriculture throughout the year, including winter, spring, and summer climate threats.

Williams, Henry J↗

DOE OSTI2021

A search for time-dependent astrophysical neutrino emission with icecube data from 2012 to 2017

High-energy neutrinos are unique messengers of the high-energy universe, tracing the processes of cosmic ray acceleration. This work presents analyses focusing on time-dependent neutrino point-source searches. A scan of the whole sky, making no prior assumption about source candidates, is performed, looking for a space and time clustering of high-energy neutrinos in data collected by the IceCube Neutrino Observatory between 2012 and 2017. No statistically significant evidence for a time-dependent neutrino signal is found with this search during this period, as all results are consistent with the background expectation. Within this study period, the blazar 3C 279, showed strong variability, inducing a very prominent gamma-ray flare observed in 2015 June. This event motivated a dedicated study of the blazar, which consists of searching for a time-dependent neutrino signal correlated with the gamma-ray emission. No evidence for a time-dependent signal is found. Hence, an upper limit on the neutrino fluence is derived, allowing us to constrain a hadronic emission model.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

Projected Changes to Extreme Precipitation Along North American West Coast From the CESM Large Ensemble

Precipitation events along the North American (NA) west coast are strongly modulated by atmospheric rivers, yet the mechanisms of their influences on the probability distributions of precipitation events are not well studied. Simulations from the Community Earth System Model (CESM) large ensemble under global warming are investigated using a moisture budget conditioned onto precipitation events for the recurrence intervals ranging from 0.1 to 50 years. In the midlatitudes, the increases in precipitation intensity and accumulation for all events over the NA west coast are predominantly controlled by moisture increases. In contrast, changes in the subtropical precipitation distributions in southwestern NA are associated with moisture increases and duration decreases for all events, with additional dynamical amplification for the heaviest precipitation events. These interpretations from the conditional moisture budget are more consistent with future projection of atmospheric rivers than the conventional mean and transient decomposition of the moisture budget.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Context matters: Natural tree mortality can lead to neighbor growth release or suppression

Where competition suppresses tree growth, mortality of adjacent trees can release the surviving individuals, leading to a growth increase. However, primary forests are complicated systems, where trees interact in both competitive and facilitative ways mediated by their size, species, and the broad ecological context in which they grow. Thus, the magnitude and even direction of growth responses to the mortality of nearby trees may vary, which has implications for our understanding of community- and ecosystem-level dynamics following mortality events. Unfortunately, although many studies focus on the impacts of light availability and general crowding on tree growth, we know relatively little about the effects of naturally occurring mortality events on the growth of neighboring trees. To address this issue, we used 40 years of data from 15 permanent forest-monitoring plots in Mt Rainier old-growth forests, comparing observed to expected radial growth of individual trees following the death of their nearest neighbor. Although we found evidence of a general growth-release response, this was not universal among all trees, with small trees in particular exhibiting growth suppression (rather than release) following neighboring tree mortality. In addition to small size, growth-suppression was more likely if the dead neighbor was the same species, consistent with facilitative effects as mediated through belowground networks. At the stand level, the average growth release after nearest neighbor mortality was greatest in low-density stands with large trees, with elevation and community composition also playing a role. Decades more monitoring could reveal how long growth release (or suppression) is sustained by individual trees following neighboring mortality events, as well as potential response lags and the role of species identity in determining whether interactions with neighbors are competitive or facilitative. Nonetheless, our results suggest that although mature trees have competitive effects on their larger neighbors, they also have an important role in supporting the ingrowth of small trees. More broadly, we demonstrate that the nature of interactions between individual neighboring trees is highly context dependent.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

An Experimental Setup for Mechanical Vibration Analysis Using VLC

This study explores the potential applications across various domains, including earthquake detection and warning systems, where the system’s sensitivity to ground vibrations can contribute to early seismic event detection. Additionally, the study paves the way of developing applications of VLC/T in mechanical vibration and stability analysis of engines and platforms, offering insights into structural integrity and performance optimization. These multifaceted applications underscore the adaptability and potential of VLC/T systems in diverse fields, heralding advancements in sensing, communication, and security technologies. To achieve this, in this study, Peak to Average Power Ratio (PAPR) is proposed to represent the impact of mechanical shocks and vibrations generated by several weights dropped onto the platform with which the receiver is fixed. Even though non-contact measurement methodology is preferred for various reasons, the proposed measurement campaign obtains the data in contact form; however, the system and signal model proposed in this study could easily be extended into non-contact form. Considering the fact that the proposed measurement campaign employs off-the-shelf products, it is cost-effective and very scalable.

Yilmaz, Ahmet Mucahit↗

DOE OSTI2026

Statistical and temporal characteristics of sawtooth events

Magnetospheric sawtooth events are characterized by periodic particle injections and magnetic dipolarizations spread quasi-simultaneously across a wide range of magnetic local times. We present a comprehensive statistical study of magnetospheric sawtooth events (STEs) during solar cycle 24 (2008–2016), extending previous catalogs and enabling solar cycle comparisons. Our results confirm that STEs predominantly occur during the rising and declining phases of the solar cycle, and are strongly associated with geomagnetic storms. Superposed epoch analysis reveals near-simultaneous particle injections across all magnetic local time sectors, but magnetic field dipolarization confined to the midnight region. These results support a scenario in which nightside tail reconnection and enhanced convection are the primary drivers of sawtooth oscillations. The localization of magnetic dipolarizations during STEs challenges global instability interpretations and suggests that STEs represent a stormtime substorm mode triggered under specific solar wind and magnetotail conditions. Superposed epoch analyses also show enhanced oxygen content in the magnetosphere during sawtooth events, but do not show a significant difference from geomagnetic storms that do not exhibit periodic behavior.

58 GEOSCIENCES↗